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Threshold of anomaly #8
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NAB calculates the threshold that maximizes the score across the benchmark. This version of ARTime is for NAB. In a real system an ART based solution would take into account the real time score and adapt based on that feedback. Ideally NAB would be extended to allow for this strategy, I raised an issue about that at numenta/NAB#391 |
If NAB calculates the threshold maximizing the score, doesn't it mean it uses the ground truth label for deciding the threshold? Doesn't it violate the unsupervised setting as the threshold is a hyperparameter? |
The threshold is not passed to the detectors. The threshold is calculated as part of the scoring algorithm. NAB assumes the detector is indicating the likelihood of an anomaly (a measure between 0 and 1). A detector like ARTime can be configured to give a binary indication of anomalies but it would be a major disadvantage given the way NAB is scored. One major issue in NAB is that it provides the range of the input values, this provides a lot of information about the future values of a given time series. |
Okay, I see. I just went through the calcScoreByThreshold function. The threshold is tried on all the prediction probabilities, and then it is decided as the one with the best score. Thanks for your clarification. |
Hi, I have a quick question about how to decide the threshold for the predicted anomaly. I see there is always a pre-defined threshold in thresholds.json for NAB. How do you decide the threshold in ARTime? Do you find it with the ROC curve or something? What do you think is a good threshold strategy (e.g., a dynamic threshold) for online settings?
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